Infrared (IR) imaging is used today in a variety of applications. For instance, law enforcement groups and militaries often use IR imaging to find persons or other targets in low-light conditions. IR imaging is also used in industrial applications to provide information about heat production and transfer in manufacturing processes.
A typical IR image device may receive an input with a very high dynamic range. In the context of IR imaging, a dynamic range may be a function of a temperature difference among multiple objects in a scene. If all of the objects are very close in temperature, then the dynamic range may be relatively low. On the other hand, if the temperature difference is large (e.g., if ice water and a hot soldering iron are in the same scene), the dynamic range may be relatively high.
Many conventional displays only have a finite number of different colors or shades that may be used to represent temperature difference within a scene. Thus, a conventional display may not be able to display a scene with a high dynamic range if the dynamic range is treated linearly.
There are a number of range compression algorithms currently available. For instance, compression using Naka-Rushton equation is commonly used in high dynamic range imagery monitors. Dynamic range compression can be applied to a scene; however, such dynamic range compression may (and often does) cause a loss of detail in the scene that is noticeable to a human user. In some instances, the loss of detail may be acceptable, but in other instances, it may be desirable to preserve the detail.